Comparative Accuracy Assessment of UAV-Derived Orthophoto, DSM, and DTM Generated with and without Ground Control Points: A Case Study of the LMTC Premises, Nepal
Aug 2026· Journal of Land Management and Geomatics Education· 0 citations
Abstract
Unmanned Aerial Vehicle (UAV) photogrammetry is increasingly used for local-scale mapping because it enables rapid generation of high-resolution orthophotos and elevation products. However, the positional and vertical quality of these products depends strongly on the georeferencing strategy, particularly the use of Ground Control Points (GCPs). This study evaluates the effect of GCPs on the accuracy of UAV-derived orthophoto, Digital Surface Model (DSM), and Digital Terrain Model (DTM) at the premises of the Land Management Training Center (LMTC), Dhulikhel, Nepal. The same UAV image block of 334 images was processed under two workflows: one using only onboard image geolocation and another using five surveyed GCPs. Eight independent checkpoints were used for accuracy assessment. Orthophoto planimetric accuracy was evaluated using checkpoint coordinates, while vertical agreement of DSM and DTM was assessed using surveyed ground elevations. In addition, pairwise checkpoint-distance analysis and supplementary object-based comparison were used to examine relative geometric differences in the orthophotos. The with-GCP orthophoto achieved a horizontal RMSEH of 0.063 m, whereas the without-GCP orthophoto showed an RMSEH of 3.507 m. Similarly, the with-GCP DSM and DTM achieved RMSEZ values of 0.131 m and 0.143 m, respectively, compared with 15.385 m and 15.347 m in the without-GCP workflow. The without-GCP orthophoto also exhibited systematic westward and northward displacement and minor scale-related geometric differences. The results demonstrate that GCP-based processing remains essential for reliable campus-scale UAV photogrammetry when the outputs are intended for measurement, terrain representation, planning, and other applications requiring dependable absolute accuracy.
The findings indicate that UAV photogrammetry combined with GIS provides a cost-effective and reliable approach for developing high-precision three-dimensional cadastral datasets that support modern land administration, urban planning, and digital city management.
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